Final Client Presentation

Dec 9, 2024

Natalie Roston

SQL Query Insights

From Project #4

Presentation Overview

  • Project Summary

  • Individual Research Interest

  • Findings

  • Implications

Project Summary

Find a single study from the WAI database where subjects of different sex, race, ethnicity, or age groups were enrolled.

Research Interest

I was particularly interested about differences in mean absorbance between race. However, exploring the Subjects dataframe taught me that very few studies were examining racial demographics.

Findings

Rosowski et al. (2012) is a study that took a unique approach to race.

SELECT Frequency, Race,
    AVG(Absorbance) AS ave_absorbance
FROM Subjects AS s
INNER JOIN Measurements AS m ON m.SubjectNumber = s.SubjectNumber
WHERE m.Identifier = "Rosowski_2012" AND s.Identifier = "Rosowski_2012" 
AND Frequency > 200 AND Frequency < 8000
GROUP BY Race, Frequency;

SELECT Race, COUNT(*) AS count
FROM Subjects
WHERE Identifier = "Rosowski_2012"
GROUP BY Race;
4 records
Race count
Caucasian 20
Black 6
Chinese 2
Asian 1

Implications

Rosowski et al.’s findings suggest that there were differences in average absorbance across “races”. However, the races are incredibly limited, and isolate Chinese from Asian.

  • What does this mean for conclusions regarding race?

  • How do we even classify race?

Research indicates that the prevalence of hearing loss does differ across races, with studies consistently showing that non-Hispanic Black individuals generally have lower rates of hearing loss compared to non-Hispanic White individuals; meaning deafness may appear less frequently in the Black population compared to the White population.

However, the data to support these claims is insufficient. Are black individuals truly less likely to experience hearing loss, or it just underreported?

Takeaways

This project reinforced the message that data isn’t everything.

Thank You!